To meet the demand for wireless data traffic having increased since deployment of 4th generation (4G) communication systems, efforts have been made to develop an improved 5th generation (5G) or pre-5G communication system. Therefore, the 5G or pre-5G communication system is also called a ‘Beyond 4G Network’ or a ‘Post Long Term Evolution (LTE) System’.
The 5G communication system is considered to be implemented in higher frequency (mmWave) bands, e.g., 60 GHz bands, so as to accomplish higher data rates. To decrease propagation loss of the radio waves and increase the transmission distance, the beamforming, massive multiple-input multiple-output (MIMO), Full Dimensional MIMO (FD-MIMO), array antenna, an analog beam forming, large scale antenna techniques are discussed in 5G communication systems.
In addition, in 5G communication systems, development for system network improvement is under way based on advanced small cells, cloud Radio Access Networks (RANs), ultra-dense networks, device-to-device (D2D) communication, wireless backhaul, moving network, cooperative communication, Coordinated Multi-Points (CoMP), reception-end interference cancellation and the like.
In the 5G system, Hybrid frequency shift keying (FSK) and quadrature amplitude modulation (FQAM) and sliding window superposition coding (SWSC) as an advanced coding modulation (ACM), and filter bank multi carrier (FBMC), non-orthogonal multiple access (NOMA), and sparse code multiple access (SCMA) as an advanced access technology have been developed.
In a wireless communication system, a reception end is required to estimate a channel of a reception signal to perform demodulation and decoding of the reception signal. The channel estimation for a downlink signal in LTE using an Orthogonal Frequency Division Multiplexing (OFDM) scheme is performed by using a Cell-specific Reference Signal (CRS).
In the LTE, Resource Elements (REs) where the CRS is received are located in the system bandwidth and arranged in the interval of six sub-carriers in a frequency domain. The CRS-based channel estimation is used for coherent demodulation of Physical Downlink Control Channel (PDCCH) or Physical Downlink Shared Channel (PDSCH), and more particularly, CRS-based fast fading channel estimation plays an important role in the coherent demodulation of the PDCCH/PDSCH of the reception end that moves at a faster rate.
The channel estimation is treated as an important technology because a majority of channel estimation scenarios assume that the channel state information is already known in the current wireless communication system. A training signal based channel estimation technique that is commonly used is a technique mainly based on linear reconstruction, such as Least Square (LS) and Minimum Mean Square Error (MMSE) methods using a reference signal. The linear reconstruction technique may have the best performance when there are large number of taps of a channel impulse response in a multi-path channel, however, according to a recent study, when using a very wide bandwidth, it is found that the linear reconstruction technique has sparse Channel Impulse Response (CIR) characteristics. Based on the above description, when a wireless communication system uses a higher dimensional signal space, the sparse CIR characteristics are provided, and in terms of performance measurement, it is found that a compressed sensing based channel estimation technique using a non-linear reconstruction algorithm is superior to a channel estimation technique using the linear reconstruction algorithm, such as the LS.